Ventana Research recently announced its 2023 Market Agenda for Analytics, continuing the guidance we have offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.
It has been exciting to follow innovations in the analytics market, but for businesses, capitalizing on these innovations can be challenging. To support this, I assert that through 2025, the majority of the workforce in more than one-half of organizations will still not be using analytics and business intelligence and, therefore, will not be executing their roles optimally. We craft our annual market agenda using our firm’s knowledge of technology vendors and products as well as our expertise in business requirements. Through this ongoing research, we offer insights and best practices that help both IT and the lines of business understand this dynamic market segment and use these technologies to their maximum potential.
Our Analytics practice encompasses six focus areas: Artificial Intelligence and Machine Learning, Business Intelligence, Embedded Analytics, Natural Language Processing, Process Mining and Streaming Analytics. Our overarching Analytics and Data Benchmark Research explores each of these topics, providing insights to guide decision-making. And if you are interested in how well vendors’ products meet organizations’ requirements, then review our Analytics and Data Value Index, which will be updated this year.
Here is our view of how each of these areas will advance in 2023.
Artificial Intelligence and Machine Learning
The application of artificial intelligence and machine learning within organizations is transforming analytics. Opportunities to take advantage of these technologies will increase over the coming year as vendors automate more AI/ML processes and further incorporate AI/ML capabilities in products. Our upcoming research will explore the extent to which these advances reduce the skills needed to reap the full benefit of AI/ML, but we assert that through 2025, AI/ML approaches will remain largely independent of business intelligence approaches, requiring three-quarters of organizations to maintain multiple, separate skill sets. For an assessment of how your organization stacks up in its use of this technology, take our short Dynamic Insights Survey on Machine Learning.
Business intelligence produces insights from data to guide decision-making, employing an increasing variety of analytic, presentation and deployment techniques. Our recent research finds that reports and dashboards are still an important component of most organizations’ BI efforts, but it also shows growing interest in additional forms of analysis, including AI/ML and natural language processing.
However, the research also shows that two-thirds (65%) of organizations lack the skills needed for AI/ML. These organizations require additional ways to take advantage of these sophisticated analytics. To support this, I assert that by 2025, 8 in 10 business intelligence vendors will include augmented intelligence to make analytics more robust and easier to use. In addition, to creating organizational agility, data and analytics processes are often supplemented with AI/ML-based assistance to enable non-technical workers to use these tools more effectively. This year we will continue to study how software vendors are incorporating these changes, and how well organizations are able to adopt these advances.
For too long, analytics and business processes have been separate. Line-of-business workers do not have access to the analytics they need to perform their roles optimally. Our research shows that in more than three-quarters of organizations, half or less of the workforce is using analytics. Organizations can more directly support the workforce in various functions by embedding analytics into business processes and applications. Not only will it make analytics more accessible, but it will enable organizations to deliver more sophisticated analytics. I assert that by 2026, more than one-half of embedded analytics processes will include AI/ML to improve line-of-business decision-making.
In our recent research, nearly three-quarters (73%) of organizations considered it important to embed analytics into business tools. BI vendors have recognized this need, and continue to invest in and improve application programming interfaces, making it easier for organizations to build custom analytics applications and for independent software vendors to include analytics in products.
Natural Language Processing
Conversational computing is becoming an increasingly common part of user interfaces. Smart speakers, mobile assistants and chatbots are propelling consumer interest in natural language capabilities. Nearly all BI vendors generate narratives based on a set of data using NLP. In some cases, vendors license these capabilities from other specialist vendors. Or, vendors developed unique capabilities. Most BI vendors also offer natural language queries, using text – and in some cases voice – as inputs to access information.
BI vendors are refining natural language processing capabilities. Future enhancement by ML will improve language recognition, making NLP more accurate and easier to use over time. We also expect to see organizations demanding more multilingual capabilities if NLP is to live up to its promise of reaching more of the workforce. We expect that by 2026, one-half of conversational analytics will incorporate multilingual capabilities to support a larger portion of organizations’ employees. We will continue to explore these issues in our Natural Language Processing Dynamic Insights research, studying these advances and how organizations are embracing them.
Most business processes are supported by software applications. These applications provide a lens into the multitude of operational processes within an organization. In recent years, we have seen the emergence of a new category of technology that mines the information and statistics collected through these processes to analyze and improve them. We assert that by 2025, one-half of organizations will examine methods to gain intelligence on the events and activities of people and machines, elevating the importance for process-mining technology. Last year we added a focus area to study how this information can be analyzed to better understand and improve the operations of an organization. We’ve launched a new Dynamic Insights study in this area, and we invite you to participate.
Data now streams into organizations from myriad sources, among them social media feeds and internet-of-things devices. The process of using that data is evolving as the amount and frequency of data collection increases. Including streaming data in analytics efforts enhances operational activities and processes to better support real-time decision-making and help make organizations more agile. We will continue to study these issues in our Streaming Data Dynamic Insights research. We expect that by 2025, one-half of organizations will incorporate streaming analytics into business processes, enabling faster response to opportunities and threats.
Analytics is having a major impact across lines of business. It is changing the customer experience, allowing organizations to use data to optimize engagement. It is transforming finance operations, providing insights on performance and enabling more forward-looking planning. It is improving hiring and retention as part of the human capital management process. Sales, marketing and supply chain functions also stand to benefit from the context and guidance that well-implemented analytics can provide. Through our 2023 Market Agenda for Analytics, we will continue our relentless focus on helping organizations realize the valuable operational improvements that can come to light through effective data analysis.
Subscribe to our Ventana Research community to stay up-to-date on our 2023 research efforts. Visit our Analytics expertise and focus areas for a detailed agenda and our continuously updated 90-day research calendar as well as additional research facts and best practices.